142 lines
4.6 KiB
Python
142 lines
4.6 KiB
Python
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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import os, sys, time
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import numpy, piexif, cv2
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from PIL import Image, ImageEnhance
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from threading import Thread
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#查找灰色区域比例
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def find_gray_area(img):
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#灰度化
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 灰色颜色范围
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lower_gray = 155
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upper_gray = 180
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# 设置灰色颜色范围
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mask = cv2.inRange(gray, lower_gray, upper_gray)
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# 计算灰色区域比例
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area = cv2.countNonZero(mask)
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return round(area / (img.shape[0] * img.shape[1]), 4)
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# 将pillow Image对象转换为opencv的image格式
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def convert_pillow_to_opencv(image):
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return cv2.cvtColor(numpy.asarray(image), 4)
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# 将opencv的image格式转换为pillow Image对象
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def convert_opencv_to_pillow(image):
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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return Image.fromarray(image)
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#锐化图片
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def sharpen_image(image, sigma):
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#高斯模糊
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blurred = cv2.GaussianBlur(image, (0, 0), sigma)
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#计算高斯模糊后的图像与原图像之间的差别
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sharpened = cv2.addWeighted(image, 1.5, blurred, -0.5, 0)
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return sharpened
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# 调整图片亮度
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def adjust_brightness(image, brightness):
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enhancer = ImageEnhance.Brightness(image)
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image = enhancer.enhance(brightness)
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return image
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# gamma correction
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def adjust_gamma(img, c=1, g=2.2):
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img = img.astype(float)
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out = img.copy()
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out /= 255.
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out = (1/c * out) ** (1/g)
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out *= 255
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out = out.astype(numpy.uint8)
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return out
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# 查找黑色区域融合算法
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def fusion_images(image, brightness_value=2.2):
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# 提升亮度将图片充分曝光，使得图片中的黑色部分更加明显，以供后续融合
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boost_brightness_image = cv2.convertScaleAbs(image, alpha=brightness_value)
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# 找出黑色区域图像信息
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lower_black =(0, 0, 0)
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upper_black = (180, 255, 46)
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hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
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h, s, v = cv2.split(hsv)
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mask = cv2.inRange(hsv, lower_black, upper_black)
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inv_mask = cv2.bitwise_not(mask)
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mask = cv2.merge([mask,mask,mask])
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inv_mask = cv2.merge([inv_mask,inv_mask,inv_mask])
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# 融合图像
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boost_brightness_image = cv2.bitwise_and(boost_brightness_image, mask)
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image = cv2.bitwise_and(image,inv_mask)
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image = cv2.add(boost_brightness_image,image)
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return image
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def enhanceImages(thread_num):
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while True:
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if len(filelist) == 0:
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break
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else:
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filename = filelist.pop()
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if filename.endswith('_1.jpg'):
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print('processing ' + filename)
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img = Image.open(os.path.join(path, filename))
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# img = img.rotate(180)
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exif = piexif.load(img.info['exif'])
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exif_bytes = piexif.dump(exif)
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# img = adjust_brightness(img, 1.8)
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img = convert_pillow_to_opencv(img)
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# img = adjust_gamma(img, 1, 2.2)
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img = fusion_images(img, 2.2)
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# img = sharpen_image(img, 5)
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img = convert_opencv_to_pillow(img)
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img.save(os.path.join(path, filename), exif=exif_bytes)
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else:
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gray_area = find_gray_area(cv2.imread(os.path.join(path, filename)))
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print('processing ' + filename + ' gray area: ' + str(gray_area))
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if gray_area > 0.3:
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print('gray area is too large, skip this image')
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os.remove(os.path.join(path, filename))
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if __name__ == '__main__':
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if len(sys.argv) < 2:
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path = '.'
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else:
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path = sys.argv[1]
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path = os.path.abspath(path)
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filelist = os.listdir(path)
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threads = []
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thread_nums = 10
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for i in range(thread_nums):
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t = Thread(target=enhanceImages, args=(str(i)))
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threads.append(t)
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t.start()
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# for file in os.listdir(path):
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# if file.endswith('116_1.jpg'):
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# img = Image.open(os.path.join(path, file))
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# img = img.rotate(180)
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# exif = piexif.load(img.info['exif'])
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# exif_bytes = piexif.dump(exif)
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# # img = adjust_brightness(img, 1.8)
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# img = convert_pillow_to_opencv(img)
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# # img = adjust_gamma(img, 1, 2.2)
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# img = fusion_images(img, 2.2)
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# # img = sharpen_image(img, 5)
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# img = convert_opencv_to_pillow(img)
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# # img.save(os.path.join(path, file), exif=exif_bytes)
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# img = convert_pillow_to_opencv(img)
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# win = cv2.namedWindow('image', cv2.WINDOW_NORMAL)
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# cv2.resizeWindow('image', 1000, 1000)
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# cv2.imshow('image', img)
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# while True:
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# if cv2.waitKey(1) & 0xFF == ord('q'):
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# break |